• The Journal of the Acoustical Society of Korea
• /
• v.41 no.3
• /
• pp.268-277
• /
• 2022

In this study, each component of flow noise source of underwater propeller installed to the scale model of the KVLCC2 is investigated and the effect of each noise source on underwater-radiated noise is quantitatively analyzed. The computation domain is set to be the same as the test section of the large cavitation tunnel in the Korea Research Institute of Ship and Ocean Engineering. First, for the high-resolution computation of flow field which is noise source region, the incompressible multiphase Delayed Detached Eddy Simulation is performed. Based on flow simulation results, the Ffowcs Williams and Hawkings integral equation is used to predict underwater-radiated noise and its validity is confirmed through the comparison with the tunnel experiment result. For the quantitative comparison on the contribution of each noise source, the spectral levels of sound pressure and power levels predicted using propeller tip-vortex cavitation, blade surface and rudder surface as the integral region of noise sources are investigated. It is confirmed that the cavitation which is monopole noise source significantly contributed to the underwater-radiated noise than propeller blades and rudder which is dipole noise source, and the rudder have more contribution than propeller blades due to the influence of the propeller wake.

• Geophysics and Geophysical Exploration
• /
• v.25 no.3
• /
• pp.129-139
• /
• 2022

Analog-based streamers for ultra-high-resolution seismic surveys are capable of additional noise ingress in water, but the specifications cannot be expanded through interconnections. Foreign-produced digital streamers have been introduced and used primarily at domestic research institutes; however, the cost is high and smooth maintenance is challenging. This study investigates the localization of ultra-high-resolution digital streamers capable of high-resolution imaging of a geological structure. A digital streamer capable of 24-bit, 10 kHz digital sampling of up to 64 channel data was developed through research and development. Various quantitative specifications of the system were designed and developed close to the benchmark model, Geometrics' GeoEel streamer, and the number of modules that make up the system was drastically reduced, reducing development costs and making it easier to use. The field applicability of the developed streamer system was evaluated in an in situ experiment conducted in the waters around the Port of Yeong-il Bay in Pohang in April 2022.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.41-63
• /
• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Journal of the Society of Disaster Information
• /
• v.19 no.3
• /
• pp.532-544
• /
• 2023

Purpose: To identify and evaluate the risk of chemical fire causative substances by using thermal analysis methods (DSC, TGA) for the hazards and physical property changes that occur when newly used biofuels are mixed with existing fuels It is to use it for identification and evaluation of the cause of fire by securing data related to the method and the hazards of the material according to it. Method: The research method used in this experiment is the differential scanning calorimeter (DSC: Difference in heat flux) through quantitative information on the caloric change from the location, shape, number, and area of peaks. flux) was measured, and the weight change caused by decomposition heat at a specific temperature was continuously measured by performing thermogravimetric analyzer (TGA: Thermo- gravimetric Analyzer). Result: First, in the heat flux graph, the boiling point of the material and the intrinsic characteristic value of the material or the energy required for decomposition can be checked. Second, as the content of biodiesel increased, many peaks were identified. Third, it was confirmed through analysis that substances with low expected boiling points were contained. Conclusion: It was shown that the physical risk of the material can be evaluated by using the risk of biodiesel, which is currently used as a new energy source, through various physical and chemical analysis techniques (DSC + TGA).In addition, it is expected that the comparison of differences between test methods and the accumulation and utilization of know-how on experiments in this study will be helpful in future studies on physical properties of hazardous materials and risk assessment of materials.

• Journal of the Microelectronics and Packaging Society
• /
• v.30 no.1
• /
• pp.71-78
• /
• 2023

The possibility of improving plating thickness distribution was investigated through quantitative consideration of bipolar electrodes without external power applied. By having the cathode tilted with respect to the anode, the potential distribution in the electrolyte solution adjacent to the cathode is different due to the difference in iR drop due to the path difference to the anode in each region of the cathode. The purpose of this study is to observe the bipolar characteristics in the case of an auxiliary anode for the non-uniform potential distribution of such a Hull cell. In particular, in order to evaluate the possibility of improving the non-uniform thickness distribution of the cathode by utilizing these bipolar characteristics, it was verified through experiments and simulations, and the electric potential and current density distribution around the bipolar electrode were analyzed. The electroplating in a Hull cell was performed for 75 min at a current density of 10 mA/cm², and the average thickness is about 16 ㎛. The standard deviation of the thickness was 10 ㎛ in the normal Hull cell without using the auxiliary anode, whereas it was 3.5 ㎛ in the case of using the auxiliary cathode. Simulation calculations also showed 8.9 ㎛ and 3.3 ㎛ for each condition, and it was found that the consistency between the experimental and simulation results was relatively high, and the thickness distribution could be improved through using the auxiliary anode by the bipolar phenomenon.

• Animal Bioscience
• /
• v.35 no.9
• /
• pp.1327-1339
• /
• 2022

Objective: Fat deposition in poultry is an important factor in production performance and meat quality research. miRNAs also play important roles in regulating adipocyte differentiation process. This study was to investigate the expression patterns of miRNAs in duck adipocytes after differentiation and explore the role of miR-214 in regulating carnitine palmitoyltransferases 2 (CPT2) gene expression during duck adipocyte differentiation. Methods: Successful systems for the isolation, culture, and induction of duck primary fat cells was developed in the experiment. Using Illumina next-generation sequencing, the miRNAs libraries of duck adipocytes were established. miRanda was used to predict differentially expressed (DE) miRNAs and their target genes. The expression patterns of miR-214 and CPT2 during the differentiation were verified by quantitative real-time polymerase chain reaction and western blot. Luciferase reporter assays were used to explore the specific regions of CPT2 targeted by miR-214. We used a miR-214 over-expression strategy in vitro to further investigate its effect on differentiation process and CPT2 gene transcription. Results: There were 481 miRNAs identified in duck adipocytes, included 57 DE miRNA candidates. And the 1,046 targets genes of DE miRNAs were mainly involved in p53 signaling, FoxO signaling, and fatty acid metabolism pathways. miR-214 and CPT2 showed contrasting expression patterns before and after differentiation, and they were selected for further research. The expression of miR-214 was decreased during the first 3 days of duck adipocytes differentiation, and then increased, while the expression of CPT2 increased both in the transcriptional and protein level. The luciferase assay suggested that miR-214 targets the 3'untranslated region of CPT2. Overexpression of miR-214 not only promoted the formation of lipid droplets but also decreased the protein abundance of CPT2. Conclusion: Current study reports the expression profile of miRNAs in duck adipocytes differentiated for 4 days. And miR-214 has been proved to have the regulator potential for fat deposition in duck.

• Korean Journal of Culture and Social Issue
• /
• v.8 no.1
• /
• pp.79-101
• /
• 2002

The present study was to investigate the psychological characteristics of Urie(義理; interpersonal morality) in Korean interpersonal relationships in terms of qualitative approach and quantitative approach. In study 1, the authors developed an open-ended questionnaire focused on Urie behavior and not Urie behavior. The results revealed that helping, trusting, and caring behaviors and historicality were the key elements of Urie relationships. On the other hand, selfish and distrusting behaviors disrupted Urie relationships. In study 2, the authors conducted video experiment in order to study how the subjects interpret and understand Urie phenomenon. This video stimulus composed of love and friendship. The main characters showed their conflicts between love and friendship. Thus, subjects were asked to answer their interpretations and understandings about what was going on according to the scene. In study 3, we made three kinds of scenarios which were constituted in conflict situation between close friends who works together at their own company. If one asks some favors to you against social justice, how do you do? Most subjects evaluated the whistle blowing behavior as moral and just. However, they evaluated the insider as not good friend. They evaluated one who did favor even though that behavior was socially unjust as good friend and having Urie. Consequently, Korean people emphasize on their human relationships in everyday life. Urie relationship is built in close and Cheong relationship.

• Tunnel and Underground Space
• /
• v.34 no.3
• /
• pp.208-217
• /
• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.50 no.2
• /
• pp.171-178
• /
• 2024

In this study, we aimed to determine the various effects of Osmanthus fragrans (O. fragrans) flower extract on the skin in order to utilize it as a cosmetic material. For this purpose, Osmanthus fragrans flower extract (OFFE) of Jeju Island was prepared and used in the experiment. The experiments were evaluated by the quantitative real-time polymerase chain reaction (qRT-PCR) and lipid droplet staining assay. First, the OFFE decreased the gene expressions of three representative pro-inflammatory cytokines (IL-8, IL-6, and IL-1α) and an inflammation-related enzyme, PTGS2 induced by poly I:C in epidermal keratinocytes. In addition, the OFFE increased the gene expression levels of collagen (COL1A1) and elastin (ELN) in dermal fibroblasts. Further, the OFFE showed the inhibitory effect in sebum production by linoleic acid in sebocytes. Therefore, from this study, it is expected that OFFE can be used as a natural cosmetic material for anti-inflammatory, anti-aging, and sebum inhibitory efficacy.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.5
• /
• pp.21-29
• /
• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.